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Analyses of 2,658 whole genomes across 38 types of cancer identify the contribution of non-coding point mutations and structural variants to driving cancer.

Understanding deregulation of biological pathways in cancer can provide insight into disease etiology and potential therapies. Here, as part of the PanCancer Analysis of Whole Genomes (PCAWG) consortium, the authors present pathway and network analysis of 2583 whole cancer genomes from 27 tumour types.

A pan-cancer genomic analysis reports the effects of structural variations on chromatin domains (TADs). Most TAD disruptions do not result in appreciable changes in expression of nearby genes.

An analysis of 2,954 genomes from 38 cancer subtypes identified 19,166 retrotransposition events in 35% of samples. Aberrant LINE-1 retrotranspositions can lead to the deletion of tumor-suppressor genes as well as the amplification of oncogenes.

In this study the authors consider the structural variants (SVs) present within cancer cases of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. They report hundreds of genes, including known cancer-associated genes for which the nearby presence of a SV breakpoint is associated with altered expression.

In somatic cells the mechanisms maintaining the chromosome ends are normally inactivated; however, cancer cells can re-activate these pathways to support continuous growth. Here, the authors characterize the telomeric landscapes across tumour types and identify genomic alterations associated with different telomere maintenance mechanisms.

Whole-genome sequencing data from more than 2,500 cancers of 38 tumour types reveal 16 signatures that can be used to classify somatic structural variants, highlighting the diversity of genomic rearrangements in cancer.

Analysis of cancer genome sequencing data has enabled the discovery of driver mutations. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium the authors present DriverPower, a software package that identifies coding and non-coding driver mutations within cancer whole genomes via consideration of mutational burden and functional impact evidence.

Multi-omics datasets pose major challenges to data interpretation and hypothesis generation owing to their high-dimensional molecular profiles. Here, the authors develop ActivePathways method, which uses data fusion techniques for integrative pathway analysis of multi-omics data and candidate gene discovery.

Day-night cycles in the biochemical composition of phytoplankton remain poorly understood. Here, Becker et al. use lipidomic and transcriptomic data from the North Pacific subtropical gyre to describe a daily cycle of production and consumption of energy-rich lipids by eukaryotic phytoplankton.

Many tumours exhibit hypoxia (low oxygen) and hypoxic tumours often respond poorly to therapy. Here, the authors quantify hypoxia in 1188 tumours from 27 cancer types, showing elevated hypoxia links to increased mutational load, directing evolutionary trajectories.

Integrative analyses of transcriptome and whole-genome sequencing data for 1,188 tumours across 27 types of cancer are used to provide a comprehensive catalogue of RNA-level alterations in cancer.

Whole-genome sequencing data for 2,778 cancer samples from 2,658 unique donors across 38 cancer types is used to reconstruct the evolutionary history of cancer, revealing that driver mutations can precede diagnosis by several years to decades.

The authors present SVclone, a computational method for inferring the cancer cell fraction of structural variants from whole-genome sequencing data.

The characterization of 4,645 whole-genome and 19,184 exome sequences, covering most types of cancer, identifies 81 single-base substitution, doublet-base substitution and small-insertion-and-deletion mutational signatures, providing a systematic overview of the mutational processes that contribute to cancer development.

With the generation of large pan-cancer whole-exome and whole-genome sequencing projects, a question remains about how comparable these datasets are. Here, using The Cancer Genome Atlas samples analysed as part of the Pan-Cancer Analysis of Whole Genomes project, the authors explore the concordance of mutations called by whole exome sequencing and whole genome sequencing techniques.

The flagship paper of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium describes the generation of the integrative analyses of 2,658 cancer whole genomes and their matching normal tissues across 38 tumour types, the structures for international data sharing and standardized analyses, and the main scientific findings from across the consortium studies.

There’s an emerging body of evidence to show how biological sex impacts cancer incidence, treatment and underlying biology. Here, using a large pan-cancer dataset, the authors further highlight how sex differences shape the cancer genome.

Viral pathogen load in cancer genomes is estimated through analysis of sequencing data from 2,656 tumors across 35 cancer types using multiple pathogen-detection pipelines, identifying viruses in 382 genomic and 68 transcriptome datasets.

Some cancer patients first present with metastases where the location of the primary is unidentified; these are difficult to treat. In this study, using machine learning, the authors develop a method to determine the tissue of origin of a cancer based on whole sequencing data.

Cancers evolve as they progress under differing selective pressures. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, the authors present the method TrackSig the estimates evolutionary trajectories of somatic mutational processes from single bulk tumour data.

Analyses of in vivo models, cell lines and patient-derived samples show that apolipoprotein B mRNA-editing catalytic subunit 3B (APOBEC3B) not only restrains lung tumor initiation but also that its upregulation is associated with resistance to targeted therapies. This study highlights the complex and context-dependent role of APOBEC3B in lung cancer.

Analysis of whole-genome sequencing data across 2,658 tumors spanning 38 cancer types shows that chromothripsis is pervasive, with a frequency of more than 50% in several cancer types, contributing to oncogene amplification, gene inactivation and cancer genome evolution.

Medulloblastomas lacking p53 do not express surface class I major histocompatibility complex (MHC-I) and are resistant to immune rejection. Tumor necrosis factor rescues MHC-I expression and synergizes with immune checkpoint inhibitors to promote rejection.

To address the question of whether a recurrent tumour is genetically similar to the tumour at diagnosis, the evolution of medulloblastoma has been studied in both an in vivo mouse model of clinical tumour therapy as well as in humans with recurrent disease; targeted tumour therapies are usually based on targets present in the tumour at diagnosis but the results from this study indicate that post-treatment recurring tumours (compared with the tumour at diagnosis) have undergone substantial clonal divergence of the initial dominant tumour clone.

Analysis of mitochondrial genomes (mtDNA) by using whole-genome sequencing data from 2,658 cancer samples across 38 cancer types identifies hypermutated mtDNA cases, frequent somatic nuclear transfer of mtDNA and high variability of mtDNA copy number in many cancers.

This study describes the integrative analysis of 111 reference human epigenomes, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression; the results annotate candidate regulatory elements in diverse tissues and cell types, their candidate regulators, and the set of human traits for which they show genetic variant enrichment, providing a resource for interpreting the molecular basis of human disease.

Medulloblastoma is the most common malignant brain tumour in children; having assembled over 1,000 samples the authors report that somatic copy number aberrations are common in medulloblastoma, in particular a tandem duplication of SNCAIP, a gene associated with Parkinson’s disease, which is restricted to subgroup 4α, and translocations of PVT1, which are restricted to Group 3.

Derailed differentiation of human-specific progenitors of the developing cerebellar rhombic lip is the cause of group 4 medulloblastoma, the most common childhood brain tumour. 

Efficient, large-scale genomic analysis is facilitated on the cloud by a computational tool with error-diagnosing and self-healing capabilities.

Michael Taylor, Marco Marra and colleagues analyze spatial tumor heterogeneity in 9 medulloblastomas, 16 high-grade gliomas and 10 renal cell carcinomas, using a combination of transcriptomic and genomic profiling of multiregional biopsies. They find that medulloblastomas have spatially homogeneous transcriptomes, whereas somatic mutations that affect genes suitable for targeted therapeutics are spatially heterogeneous.

Sonic Hedgehog medulloblastoma (Shh-MB) comprises four subtypes each with distinct clinical traits. Here the authors characterize the genome, transcriptome, and methylome of Shh-MB subtypes, revealing a complex fusion landscape and the molecular convergence of MYCN and cAMP signaling pathways.

KRAS wildtype metastatic pancreatic ductal adenocarcinoma (mPDAC) could represent a distinct molecular entity from other PDACs. Here, the authors analyse KRAS wildtype mPDAC tumours using genomics and transcriptomics and find molecular similarities with cholangiocarcinomas.

Wilms tumour is a rare renal neoplasm that primarily affects children but the genomic changes responsible for its development are currently largely unknown. In this study, the authors identify somatic mutations of the MLLT1gene that are potentially involved in the aetiology of a subset of Wilms tumours.

A large-scale genomics study shows that the cell of origin and founding mutations determine disease subtype and lead to the expression of multiple haematopoietic lineage-defining antigens in mixed phenotype acute leukaemia.

Primary biliary cirrhosis is an autoimmune liver disease with poor therapeutic options. Here Cordell et al. a perform meta-analysis of European genome-wide association studies identifying six novel risk loci and a number of potential therapeutic pathways.